ArticleGenome medicine2018
Integrated time course omics analysis distinguishes immediate therapeutic response from acquired resistance.
Article in Genome medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.
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Who cites it
23 citing papers in PubMed, 33 citations in OpenAlex.
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- [Research progress on the mechanisms of resistance to cetuximab targeted therapy in head and neck squamous cell carcinoma].Lin chuang er bi yan hou tou jing wai ke za zhi = Journal of clinical otorhinolaryngology head and neck surgery · 2025Review
- Economic Evaluation of Penpulimab Plus Paclitaxel and Carboplatin Combination Therapy as First-Line Treatment for Locally Advanced or Metastatic Squamous Non-small Cell Lung Cancer in China.Clinical drug investigation · 2025Article
- Inferring cellular and molecular processes in single-cell data with non-negative matrix factorization using Python, R and GenePattern Notebook implementations of CoGAPS.Nature protocols · 2023Review
- A novel intronic circular RNA circFGFR1Journal of translational medicine · 2023Article
- Making In Vitro Tumor Models Whole Again.Advanced healthcare materials · 2023Review
- RNA methylation and cellular response to oxidative stress-promoting anticancer agents.Cell cycle (Georgetown, Tex.) · 2023Review
- Model-informed experimental design recommendations for distinguishing intrinsic and acquired targeted therapeutic resistance in head and neck cancer.NPJ systems biology and applications · 2022Article
- RNA Sequencing and Cell Models of Virus-Associated Cancer (Review).Sovremennye tekhnologii v meditsine · 2022Review
- PD-L1 is upregulated via BRD2 in head and neck squamous cell carcinoma models of acquired cetuximab resistance.Head & neck · 2021Article
- Subclone Eradication Analysis Identifies Targets for Enhanced Cancer Therapy and Reveals L1 Retrotransposition as a Dynamic Source of Cancer Heterogeneity.Cancer research · 2021Article
- Transfer learning between preclinical models and human tumors identifies a conserved NK cell activation signature in anti-CTLA-4 responsive tumors.Genome medicine · 2021Article
- The functional GRHL3-filaggrin axis maintains a tumor differentiation potential and influences drug sensitivity.Molecular therapy : the journal of the American Society of Gene Therapy · 2021Article
- Forecasting cellular states: from descriptive to predictive biology via single-cell multiomics.Current opinion in systems biology · 2021Article
- Precision Medicine Approaches to Overcome Resistance to Therapy in Head and Neck Cancers.Frontiers in oncology · 2021Review
- Matrix factorization and transfer learning uncover regulatory biology across multiple single-cell ATAC-seq data sets.Nucleic acids research · 2020Article
- Integrated single-cell and bulk gene expression and ATAC-seq reveals heterogeneity and early changes in pathways associated with resistance to cetuximab in HNSCC-sensitive cell lines.British journal of cancer · 2020Article
- Article
- Extracellular Vesicles Released by Tumor Endothelial Cells Spread Immunosuppressive and Transforming Signals Through Various Recipient Cells.Frontiers in cell and developmental biology · 2020Article
Corrections and comments
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Authors and funding
16 authors at 7 institutions in 3 countries.
Funding
Abstract
backgroundTargeted therapies specifically act by blocking the activity of proteins that are encoded by genes critical for tumorigenesis. However, most cancers acquire resistance and long-term disease remission is rarely observed. Understanding the time course of molecular changes responsible for the development of acquired resistance could enable optimization of patients' treatment options. Clinically, acquired therapeutic resistance can only be studied at a single time point in resistant tumors.
methodsTo determine the dynamics of these molecular changes, we obtained high throughput omics data (RNA-sequencing and DNA methylation) weekly during the development of cetuximab resistance in a head and neck cancer in vitro model. The CoGAPS unsupervised algorithm was used to determine the dynamics of the molecular changes associated with resistance during the time course of resistance development.
resultsCoGAPS was used to quantify the evolving transcriptional and epigenetic changes. Applying a PatternMarker statistic to the results from CoGAPS enabled novel heatmap-based visualization of the dynamics in these time course omics data. We demonstrate that transcriptional changes result from immediate therapeutic response or resistance, whereas epigenetic alterations only occur with resistance. Integrated analysis demonstrates delayed onset of changes in DNA methylation relative to transcription, suggesting that resistance is stabilized epigenetically.
conclusionsGenes with epigenetic alterations associated with resistance that have concordant expression changes are hypothesized to stabilize the resistant phenotype. These genes include FGFR1, which was associated with EGFR inhibitors resistance previously. Thus, integrated omics analysis distinguishes the timing of molecular drivers of resistance. This understanding of the time course progression of molecular changes in acquired resistance is important for the development of alternative treatment strategies that would introduce appropriate selection of new drugs to treat cancer before the resistant phenotype develops.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.